This paper considers identical parallel machines scheduling problem with past-sequence-dependent setup times, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of the processing times of the jobs already processed and its scheduled position on the corresponding machine. In addition, the setup time of a job on each machin...

The notion of approximation problems was formally introduced by Johnson [3] in his pioneering paper on the approximation of combinatorial optimization problems, and it was also suggested a possible classification of optimization problems on grounds of their approximability properties. Since then, it was clear that, even though the decision versions of most NP-hard optimization problems are poly...

This paper addresses a new mixed integer nonlinear and linear mathematical programming economic lot sizing and scheduling problem in distributed permutation flow shop problem with number of identical factories and machines. Different products must be distributed between the factories and then assignment of products to factories and sequencing of the products assigned to each factory has to be d...

Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. I...

Memetic algorithms are population-based metaheuristics aimed to solve hard optimization problems. These techniques are explicitly concerned with exploiting available knowledge in order to achieve the most effective resolution of the target problem. The rationale behind this optimization philosophy, namely the intrinsic theoretical limitations of problem-unaware optimization techniques, is prese...

In this paper a new technique for the solutions of hard computational problems in bioinformatics is investigated. This is the $-calculus process algebra for problem solving that applies the cost performance measures to converge to optimal solutions with minimal problem solving costs. We demonstrate that the $-calculus generic search method, called the kΩ-optimization, can be used to solve gene ...

In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...

The Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization and nonlinear problem seeking to service a number of customers with a fleet of vehicles. CVRP is an important problem in the fields of transportation, distribution and logistics. Usually, the goal is delivering goods located at a central depot to customers who have placed orders. This transportation optimization prob...

The Minimum Label Spanning Tree Problem is a well known combinatorial optimization problem, having applications in telecommunication network design and data compression. The problem is NP-hard and cannot be approximated within a constant factor. In this work we present the application of ant colony optimization to this problem. Different pheromone models and construction mechanisms are introduc...